A Two-Segment Approximation Algorithm for Separable Convex Programming with Linear Constraints.

Abstract

Document discusses a new algorithm for the separable convex programming with linear constraints. This is based on the approximation of the objective function by at most two linear pieces in the neighborhood of the current feasible solution. The two segments will be adaptively defined rather than predecided fixed grids. If, furthermore, the objective function is differentiable, and one introduces a non-Archimedean infinitesimal, the algorithm generates a sequence of feasible solutions every cluster point of which is an optimal solution. Computational tests on the problem with up to 196 non-linear variables is presented. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1984
Accession Number
ADA146215

Entities

People

  • Abraham Charnes
  • I. Ali
  • Taesoo Song

Organizations

  • University of Texas at Austin

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Computations
  • Computer Programming
  • Convergence
  • Convex Programming
  • Evolutionary Algorithms
  • Heuristic Methods
  • Linear Programming
  • Numbers
  • Real Numbers
  • Sequences
  • Simplex Method
  • United States
  • United States Government
  • Universities

Fields of Study

  • Computer science

Readers

  • Computer Vision.
  • Linear Algebra
  • Mathematical Modeling and Probability Theory.